Abstract 6623: Ultra-deep multi-omics sequencing to identify drivers of glioblastoma recurrence and evolution

Abstract Glioblastoma (GBM) is the most prevalent and deadliest form of brain tumor with a median patient survival of 15 months after diagnosis. However, the mechanisms of tumor recurrence and the molecular alterations contributing to therapy resistance remain poorly understood. To address this challenge, we performed ultra-deep whole transcriptome, whole genome, and nanopore long-read sequencing of matched primary and recurrent GBMs of 12 adult patients with matching germline controls (fresh-frozen blood) and patient treatment and clinical histories. We generated a multi-omics datasets of single nucleotide variants (SNVs), structural variants (SVs), copy number alterations, genome-wide DNA methylation patterns, and transcriptomics. Our long-read sequencing data provided nucleotide-level methylation data to analyze genome-wide methylation patterns and high-quality structural variants for profiling complex genomic rearrangements and identifying episomes. Major changes between primary and recurrent samples in SVs, such as selection for EGFR translocations in recurrent tumors, and nucleotide-level methylation patterns, such as increased methylation of the FUBP1 and IDH1 promoters in recurrent tumors, were only detectable using long-read sequencing strategies, emphasizing the value of long-read sequencing in evolutionary analyses. We identified distinct mutational processes responsible for primary and recurrent tumor mutations and driving evolution of a recurrent tumor with therapeutic resistance. We found evidence of multi-omics dysregulation of oncogenes including promoter silencing by methylation and SVs selecting for the EGFR-vIII variant. Extensive inter- and intra-tumor heterogeneity and evidence of clonal selection in recurrent tumors was detected from ultra-deep whole genome sequencing, including selection for EGFR SNVs and PTEN and RB1 copy number deletions in recurrent tumors. We found an enrichment of SVs and epigenetic modifications in recurrent tumors, such as increased methylation of CDK4 and CDK6 promoters, and a depletion of classical tumor drivers, such as EGFR and CDK4 amplifications. Our integrative pathway analysis of multi-omics data of differentially methylated and expressed genes between primary and recurrent GBMs prioritized several glioma pathways enriched in recurrent tumors associated with glioma processes such as gliogenesis and angiogenesis. Our cohort had comparable mutation rates and processes as the Glioma Longitudinal Analysis (GLASS) consortium of paired primary-recurrent GBMs. However, our unique dataset of paired primary and recurrent GBMs provides an unprecedented multi-omics, multi-layered view of the genetic, transcriptomic, and epigenetic processes of GBM evolution. Citation Format: Alexander Bahcheli, Philip Zuzarte, Sunit Das, Jared Simpson, Jüri Reimand. Ultra-deep multi-omics sequencing to identify drivers of glioblastoma recurrence and evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6623.

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